Non-Topical Factors in Information Access

Research in information retrieval has traditionally concentrated on making assumptions about the content of documents based on very shallow semantic analysis through word occurrence statistics of various kinds. But texts are more than bags of words, and the semantic analysis information retrieval systems typically used is overly simple. There is ample reason to try to broaden the view of what text is and why. Better content analysis alone will not be enough. Texts are more than their meaning. Texts have structure, they have context, they are written in a style conformant or discordant to a genre they are to be understood in, they may be carefully written or hastily thrown together, they are written by various types of agent for various reasons. Besides information to be found in the text or from the author, texts are used by readers of various backgrounds, for various reasons, and with varying degree of satisfaction. This paper outlines a framework within which to nd more knowledge from texts than an approximation of their topic, and gives examples of how to use this knowledge to design useful tools for information access. Arguably, the most important characteristic of a document is what it is about. The topic of a document is the most important criterion for selecting it from a collection. How to model the topic of documents in a collection eeectively is the most obvious goal for most research in information retrieval. But researchers in the eld are keenly aware of the fact that the interaction of information seeking users and the tools to access information sources is important in itself. Information can be sought for various reasons and with various ideas of how to determine what documents or other information bearing units are relevant. Indeed, no interactive information access system can disregard the requirements posed by users { and this is most often understood to allow users to request documents from the collection with a minimum of complexity, by mod